Fostering engineering and science students' and teachers' systems thinking and conceptual modeling skills.

As science and technology create an ecosystem that is becoming increasingly more knowledge-intensive, complex, and interconnected, the next generation science standards include systems thinking and systems modeling among 21st skills that should be fostered. We examined the effect of an online cross-disciplinary learning process on the development of systems thinking and modeling skills among engineering students and engineering and science teachers. The study, which used quantitative and qualitative tools, included 55 participants who performed four food-related learning assignments and created conceptual models in Object-Process Methodology. Their responses to online assignments were analyzed along with their perceptions, captured via a reflection questionnaire. The online learning process in this study effectively enhanced systems thinking and modeling skills of all learners, including those with no relevant background. One main conclusion that extends beyond the online learning was that imparting the basics of systems thinking and conceptual modeling skills can be achieved even within a short period of time-less than one semester. The contribution of the study is the formation of theoretical and practical frameworks for the integration of an cross-disciplinary model-based systems engineering online assignments into engineering and science curricula.

Object-Process Methodology as an Alternative to Human Factors Task Analysis.

OBJECTIVE: We define and demonstrate the use of OPM-TA-a model-based task analysis (TA) framework that uses object-process methodology (OPM) ISO 19450 as a viable alternative to traditional TA techniques. BACKGROUND: A variety of different TA methods exist in human factors engineering, and several of them are often applied successively for a broad task representation, making it difficult to follow. METHOD: Using OPM-TA, we modeled how an International Space Station (ISS) astronaut would support extravehicular activities using the existing robotic arm workstation with a new control panel and an electronic procedure system. The modeling employed traditional TA methods and the new OPM-TA approach, enabling a comparison between them. RESULTS: While the initial stages of modeling with OPM-TA follow those of traditional TA, OPM-TA modeling yields an executable and logically verifiable model of the entire human-robot system. Both OPM's hierarchical set of diagrams and the equivalent, automatically generated statements in a subset of natural language text specify how objects and processes relate to each other at increasingly detailed levels. The graphic and textual OPM modalities specify the system's architecture, which enables its function and benefits its users. To verify the model logical correctness model, we executed it using OPM's simulation capability. CONCLUSION: OPM-TA was able to unify traditional TA methods and expand their capabilities. The formal yet intuitive OPM-TA approach fuses and extends traditional TA methods, which are not amenable to simulation. It therefore can potentially become a widely used means for TA and human-machine procedure development and testing.

Modeling with Real-Time Informative Feedback: Implementing and Evaluating a New Massive Open Online Course Component.

As part of the design, development, and deployment of a massive open online course (MOOC) on model-based systems engineering, we introduced MORTIF-Modeling with Real-Time Informative Feedback, a new learning-by-doing feature that enables the learner to model, receive detailed feedback, and resubmit improved solutions. We examined the pedagogical usability of MORTIF by investigating characteristics of participants working with it, and their perceived contribution, preferred question type, and learning style. The research included 295 participants and applied the mixed-methods approach, using MOOC server data and online questionnaires. Analyzing 12,095 submissions, we found increasing frequency of using the model resubmitting option. Students ranked MORTIF as the highest of six question types in terms of preference and perceived contribution level. Nine learning style categories were identified and classified based on students' verbal explanations regarding their preference of MORTIF over the other question types. MORTIF has been effective in promoting meaningful learning, supporting our hypothesis that the combination of active learning with real-time informative feedback is a learning mode that students eagerly embrace and benefit from. The benefits we identified for using MORTIF include active learning, provision of meaningful immediate feedback to the learner, the option to use the feedback on the spot and resubmitting an improved model, and its suitability for a variety of learning styles.

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure.

The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer's ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015-Object Process Methodology as our conceptual modeling framework.

Operation room tool handling and miscommunication scenarios: an object-process methodology conceptual model.

OBJECTIVE: Errors in the delivery of medical care are the principal cause of inpatient mortality and morbidity, accounting for around 98,000 deaths in the United States of America (USA) annually. Ineffective team communication, especially in the operation room (OR), is a major root of these errors. This miscommunication can be reduced by analyzing and constructing a conceptual model of communication and miscommunication in the OR. We introduce the principles underlying Object-Process Methodology (OPM)-based modeling of the intricate interactions between the surgeon and the surgical technician while handling surgical instruments in the OR. This model is a software- and hardware-independent description of the agents engaged in communication events, their physical activities, and their interactions. The model enables assessing whether the task-related objectives of the surgical procedure were achieved and completed successfully and what errors can occur during the communication. METHODS AND MATERIAL: The facts used to construct the model were gathered from observations of various types of operations miscommunications in the operating room and its outcomes. The model takes advantage of the compact ontology of OPM, which is comprised of stateful objects - things that exist physically or informatically, and processes - things that transform objects by creating them, consuming them or changing their state. The modeled communication modalities are verbal and non-verbal, and errors are modeled as processes that deviate from the "sunny day" scenario. Using OPM refinement mechanism of in-zooming, key processes are drilled into and elaborated, along with the objects that are required as agents or instruments, or objects that these processes transform. The model was developed through an iterative process of observation, modeling, group discussions, and simplification. RESULTS: The model faithfully represents the processes related to tool handling that take place in an OR during an operation. The specification is at various levels of detail, each level is depicted in a separate diagram, and all the diagrams are "aware" of each other as part of the whole model. Providing ontology of verbal and non-verbal modalities of communication in the OR, the resulting conceptual model is a solid basis for analyzing and understanding the source of the large variety of errors occurring in the course of an operation, providing an opportunity to decrease the quantity and severity of mistakes related to the use and misuse of surgical instrumentations. Since the model is event driven, rather than person driven, the focus is on the factors causing the errors, rather than the specific person. This approach advocates searching for technological solutions to alleviate tool-related errors rather than finger-pointing. Concretely, the model was validated through a structured questionnaire and it was found that surgeons agreed that the conceptual model was flexible (3.8 of 5, std=0.69), accurate, and it generalizable (3.7 of 5, std=0.37 and 3.7 of 5, std=0.85, respectively). CONCLUSION: The detailed conceptual model of the tools handling subsystem of the operation performed in an OR focuses on the details of the communication and the interactions taking place between the surgeon and the surgical technician during an operation, with the objective of pinpointing the exact circumstances in which errors can happen. Exact and concise specification of the communication events in general and the surgical instrument requests in particular is a prerequisite for a methodical analysis of the various modes of errors and the circumstances under which they occur. This has significant potential value in both reduction in tool-handling-related errors during an operation and providing a solid formal basis for designing a cybernetic agent which can replace a surgical technician in routine tool handling activities during an operation, freeing the technician to focus on quality assurance, monitoring and control of the cybernetic agent activities. This is a critical step in designing the next generation of cybernetic OR assistants.

Conceptual modeling of mRNA decay provokes new hypotheses.

Biologists are required to integrate large amounts of data to construct a working model of the system under investigation. This model is often informal and stored mentally or textually, making it prone to contain undetected inconsistencies, inaccuracies, or even contradictions, not much less than a representation in free natural language. Using Object-Process Methodology (OPM), a formal yet visual and humanly accessible conceptual modeling language, we have created an executable working model of the mRNA decay process in Saccharomyces cerevisiae, as well as the import of its components to the nucleus following mRNA decay. We show how our model, which incorporates knowledge from 43 articles, can reproduce outcomes that match the experimental findings, evaluate hypotheses, and predict new possible outcomes. Moreover, we were able to analyze the effects of the mRNA decay model perturbations related to gene and interaction deletions, and predict the nuclear import of certain decay factors, which we then verified experimentally. In particular, we verified experimentally the hypothesis that Rpb4p, Lsm1p, and Pan2p remain bound to the RNA 3'-untranslated region during the entire process of the 5' to 3' degradation of the RNA open reading frame. The model has also highlighted erroneous hypotheses that indeed were not in line with the experimental outcomes. Beyond the scientific value of these specific findings, this work demonstrates the value of the conceptual model as an in silico vehicle for hypotheses generation and testing, which can reinforce, and often even replace, risky, costlier wet lab experiments.

Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure-the objects that comprise the system, and behavior-how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point-the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model.

A methodology for eliciting and modeling exceptions.

Exceptions in safety-critical systems must be addressed during conceptual design and risk analysis. We developed a conceptual model of exceptions, a methodology for eliciting and modeling exceptions, and templates for modeling them in an extension of the Object-Process Methodology (OPM)-a system analysis and design methodology and language that uses a single graphical model for describing systems, including their timing exceptions, which has been shown to be an effective modeling methodology. Using an antibiotics treatment guideline as a case study, we demonstrate the value of our approach in eliciting and modeling exceptions that occur in clinical care systems.

Situation-Based Access Control: privacy management via modeling of patient data access scenarios.

Access control is a central problem in privacy management. A common practice in controlling access to sensitive data, such as electronic health records (EHRs), is Role-Based Access Control (RBAC). RBAC is limited as it does not account for the circumstances under which access to sensitive data is requested. Following a qualitative study that elicited access scenarios, we used Object-Process Methodology to structure the scenarios and conceive a Situation-Based Access Control (SitBAC) model. SitBAC is a conceptual model, which defines scenarios where patient's data access is permitted or denied. The main concept underlying this model is the Situation Schema, which is a pattern consisting of the entities Data-Requestor, Patient, EHR, Access Task, Legal-Authorization, and Response, along with their properties and relations. The various data access scenarios are expressed via Situation Instances. While we focus on the medical domain, the model is generic and can be adapted to other domains.

Conceptual modeling in systems biology fosters empirical findings: the mRNA lifecycle.

One of the main obstacles to understanding complex biological systems is the extent and rapid evolution of information, way beyond the capacity individuals to manage and comprehend. Current modeling approaches and tools lack adequate capacity to model concurrently structure and behavior of biological systems. Here we propose Object-Process Methodology (OPM), a holistic conceptual modeling paradigm, as a means to model both diagrammatically and textually biological systems formally and intuitively at any desired number of levels of detail. OPM combines objects, e.g., proteins, and processes, e.g., transcription, in a way that is simple and easily comprehensible to researchers and scholars. As a case in point, we modeled the yeast mRNA lifecycle. The mRNA lifecycle involves mRNA synthesis in the nucleus, mRNA transport to the cytoplasm, and its subsequent translation and degradation therein. Recent studies have identified specific cytoplasmic foci, termed processing bodies that contain large complexes of mRNAs and decay factors. Our OPM model of this cellular subsystem, presented here, led to the discovery of a new constituent of these complexes, the translation termination factor eRF3. Association of eRF3 with processing bodies is observed after a long-term starvation period. We suggest that OPM can eventually serve as a comprehensive evolvable model of the entire living cell system. The model would serve as a research and communication platform, highlighting unknown and uncertain aspects that can be addressed empirically and updated consequently while maintaining consistency.

Eliciting and characterizing scenarios of disclosure of private health data.

Sensitive health information is kept in Electronic Health Records (EHRs) which makes the data accessible, enabling its transfer against patient consent. Hence, the need for privacy-preserving mechanisms is a top priority. As a first step towards the development of privacy-preserving access control language, we used qualitative research methods to characterize scenarios of requests for disclosure of patient data and identify the entities involved, the context of the request, and the requested data.